Hugging Face Trending Papers August 10, 2026

Beyond the Capability Boundary: Zeroth-Order Optimization for Self-Evolving LLM Agents

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Self-evolving methods improve the capabilities of LLM agents by sampling trajectories from the underlying LLMs and learning from these trajectories. However, these methods struggle to learn beyond the inherent capability boundary of the agents, since the agents cannot sample correct trajectories on difficult examples for further improvements.

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arXiv Machine Learning

Aug 11

Beyond the Capability Boundary: Zeroth-Order Optimization for Self-Evolving LLM Agents

arXiv:2608. 09292v1 Announce Type: new Abstract: Self-evolving methods improve the capabilities of LLM agents by sampling trajectories from the underlying LLMs and learning from these trajectories.

By Bingzhen Liu, Xiaomeng Fan, Yuwei Wu, Zhi Gao, Mingyang Gao, Chuanhao Li, Yunde Jia

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arXiv AI

Jun 4

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By Tao Ren, Weiyao Luo, Hui Yang, Rongzhi Zhu, Xiang Huang, Yuchuan Wu, Bingxue Chou, Jieping Ye, Jiafeng Liang, Yongbin Li, Yijie Peng

llms agents reinforcement-learning fine-tuning

arXiv Machine Learning

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Agentic ESOpt: Fine-Tuning Long-Horizon LLM Agents with Minimal GPU Requirements

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llms agents reinforcement-learning fine-tuning

arXiv AI

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SBCO: Self-Supervised, Verifier-Grounded Harness Optimization For Planning Agents

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arXiv Machine Learning

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By Zhiyuan Wang, Shengcai Liu, Jiahao Wu, Ning Lu, Hui Ouyang, Shaofeng Zhang, Haoze Lv, Ke Tang

llms agents reinforcement-learning fine-tuning benchmarks

arXiv Machine Learning

Jul 27

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning

arXiv:2607. 21971v1 Announce Type: new Abstract: Test-time scaling through iterative self-evolution with environment feedback, as demonstrated by AlphaEvolve, shows remarkable performance gains.

By Shujin Wu, Cheng Qian, Xiusi Chen, Heng Ji

llms reinforcement-learning benchmarks

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Beyond the Capability Boundary: Zeroth-Order Optimization for Self-Evolving LLM Agents

Scaling Self-Evolving Agents via Parametric Memory

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